Developing a Laboratory for Engineering Education in Mechatronics
Bibliographic record
Abstract
This paper reports the development processof a laboratory in mechatronics for mechanicalengineering education at the undergraduate level. The labwas developed to meet two primary objectives: creatingand enhancing opportunities for student skill developmentin the context of two key Canadian EngineeringAccreditation Board (CEAB) graduate attributes, andproviding hands-on experience in mechatronic design inline with current trends in mechatronics education andindustrial practice.Of the twelve CEAB attributes, “Design” and “Useof Engineering Tools” are most compatible with the labin mechatronics. The mechatronics lab was developed,providing occasion for students to engage in engineeringdesign work and use modern engineering equipment inthe process.In step with trends and requirements of industry,mechatronics education in recent years has made a shifttoward integration of microcontrollers with sensors andactuators as integral parts of mechatronics design work.Mechatronics equipment has also become more widelyavailable at lower cost, enabling broader access andcreating the possibility of replicating industrial projectson a smaller scale within a university lab. Themechatronics lab reflects these developments.This paper also explores the continuity of learningoutcomes from lectures to labs and the connectionbetween these outcomes and graduate attributes. Itoutlines some of the issues and limitations encountered.We also report on qualitative student experience based oninteractions and informal student feedback.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".